Radar systems typically use digital signal processing to cancel interfering (e.g. jamming) signals from a main channel of a radar array by adaptively weighting sampled demodulated outputs of one or more auxiliary channels and subtracting them from the main channel's output. Deep cancellation of jamming signals, however, requires that the frequency responses of the main and auxiliary channels be highly matched across the instantaneous bandwidth. Fixed amplitude and phase offsets do not limit cancellation. Frequency-dependent channel-to-channel mismatches, however, do limit cancellation. These frequency-dependent mismatches may include amplitude ripple, phase ripple, linear amplitude slope, and linear phase slope, by way of example only. A single adaptive weight in each auxiliary channel can provide adequate cancellation at the center of the instantaneous bandwidth, however, the net cancellation may be inadequate if the bandwidth and post-calibration frequency-dependent mismatches are sufficiently large.
Mismatch across a broad instantaneous bandwidth may be mitigated by implementing an equalizer at the output of each channel's digital demodulator to compensate for passband mismatches that are either constant or that change very slowly over long periods of time as the equipment ages or changes temperature. An equalizer may be a finite impulse response (FIR) filter, operating at the in-phase/quadrature (I/Q) sample rate, and operative to modify the frequency response of each channel so that all channel responses approximately match a common reference response shape. However, conventional channel equalization cannot adequately account for the difference in time delay between the jammer signal in one channel and the jammer signal in every other channel because these delays continually differ as the radar rotates.
A conventional solution to this problem is to replace the single adaptive weight in each auxiliary channel with an adaptive FIR filter that implements a complex adaptive weight in each tap. Adaptive computation of these weights will then automatically match the various channel responses to maintain deep cancellation across the instantaneous bandwidth, despite changing jammer angles due to array rotation. Typically, the total duration of the FIR is chosen to be greater than the inverse of the shortest expected passband ripple period. The total number of taps is then given by this time duration divided by the I/Q sample period T. Depending on the shortest ripple period expected, a large number of taps may be required, with each tap requiring an adaptive weight. The large number of taps needed to handle a combination of slow and fast mismatches increases computational complexity and requires a large amount of jammer signal data to adequately train the adaptive weights. Alternative techniques are desired.